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Tissue multifractality and hidden Markov model based integrated framework for optimum precancer detection.

Sabyasachi Mukhopadhyay1, Nandan K Das1,2, Indrajit Kurmi3

  • 1Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal, India.

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Summary

A novel hidden Markov model (HMM) approach effectively distinguishes precancerous cervical tissue using fractal analysis of optical properties. This method shows superior performance over support vector machine (SVM) models for cancer detection.

Keywords:
hidden Markov modelinverse analysis on light scatteringmultifractal detrended fluctuation analysissupport vector machinetissue characterization

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Area of Science:

  • Biomedical Optics
  • Medical Imaging Analysis
  • Cancer Diagnostics

Background:

  • Accurate discrimination of precancerous cervical tissue is crucial for effective cancer prevention.
  • Current diagnostic methods may benefit from advanced analytical techniques for improved sensitivity.

Purpose of the Study:

  • To apply a hidden Markov model (HMM) integrated with multifractal analysis for enhanced discrimination of precancerous cervical tissue.
  • To evaluate the efficacy of fractal parameters as biomarkers for cervical cancer detection.

Main Methods:

  • Derivation of multifractal tissue optical properties using Born approximation-based inverse light scattering.
  • Computation of generalized Hurst exponent and singularity spectrum width via multifractal detrended fluctuation analysis (MFDFA).
  • Integration of MFDFA parameters with Hidden Markov Models (HMM) and Support Vector Machines (SVM) for classification.

Main Results:

  • The MFDFA-HMM integrated model demonstrated significantly improved discrimination between normal and precancerous cervical tissues.
  • The proposed methodology effectively utilizes fractal parameters as biomarkers.
  • Performance of the MFDFA-HMM model surpassed that of the MFDFA-SVM model.

Conclusions:

  • The MFDFA-HMM approach offers a promising, highly effective method for early detection of cervical cancer.
  • Multifractal analysis combined with HMM provides a robust tool for biomedical image analysis in oncology.
  • Fractal parameters derived from optical properties can serve as valuable biomarkers for precancerous tissue identification.